The exemplary embodiment relates to a system and method for generating a model for predicting the state of a set of cells, based on incomplete data. It finds particular application in connection with a parking occupancy detection system and will be described with particular reference thereto. However, it is to be appreciated that the system and method are applicable to other occupancy prediction problems.
Parking zone management systems have been developed which include a vehicle sensor for each parking space in a parking zone. The vehicle sensors each determine the occupancy status of the respective parking space, i.e., whether or not the space is free or is occupied by a vehicle. The occupancy data is communicated to a centralized system, allowing occupancy information to be made available, for example, to inform potential users of the parking zone that there are parking spaces available in the parking zone, or to provide information about a set of neighboring parking zones.
One problem which arises is that the vehicle sensors are prone to failure. When a sensor fails, it no longer reports the occupancy state (occupied or available) of its respective parking space. Thus, the number of available parking spaces in a parking zone is not accurately reported to the centralized system when on or more of the sensors fails. One way to address this problem is to assume that the occupancy of a non-reporting parking space can be predicted based on the output of the reporting sensors. A problem with this approach, which has been identified by the present applicants, is that this approach does not always accurately predict the occupancy status of parking spaces, since full spaces and empty spaces do not have missing measurements with equal probability.
Since the availability of parking spaces may be insufficient or barely sufficient to meet the demand of drivers, particularly during peak times, it would be desirable to have an accurate evaluation of the availability and location of parking spaces.
The present system and method address this problem and others by generating a model for predicting occupancy status of a set of cells, such as parking spaces, when the reporting data is incomplete.